Nicolas Thiebaut
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Nicolas Thiebaut Email & Phone Number

Adjunct Professor - Machine Learning Operations at University of San Francisco
Location: San Francisco, California, United States 10 work roles 3 schools
2 work emails found @hired.com 3 phones found area 368 and 949 LinkedIn matched
✓ Verified August 2026 4 data sources Profile completeness 100%

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Work email n****@hired.com
Direct phone (368) ***-****
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Current company
Role
Adjunct Professor - Machine Learning Operations
Location
San Francisco, California, United States

Who is Nicolas Thiebaut? Overview

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Nicolas Thiebaut is listed as Adjunct Professor - Machine Learning Operations at University of San Francisco, based in San Francisco, California, United States. AeroLeads shows a work email signal at hired.com, phone signal with area code 368, 949, and a matched LinkedIn profile for Nicolas Thiebaut.

Nicolas Thiebaut previously worked as Senior Machine Learning Engineering at Roblox and Adjunct Professor - Deep Learning at Université De Technologie De Troyes. Nicolas Thiebaut holds Doctor Of Philosophy (Phd), Theoretical Physics from Paris-Sud University (Paris Xi).

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{first}@hired.com
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Profile bio

About Nicolas Thiebaut

Machine Learning practitioner specializing in deep learning, natural language processing, and AIexplainability and fairness.

Listed skills include Data Science, Machine Learning, Physics, Python, and 13 others.

Current workplace

Nicolas Thiebaut's current company

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University of San Francisco
University Of San Francisco
Adjunct Professor - Machine Learning Operations
San Francisco, CA, US
AeroLeads page
10 roles

Nicolas Thiebaut work experience

A career timeline built from the work history available for this profile.

Adjunct Professor - Machine Learning Operations

Current

San Francisco, Ca, Us

Responsible for the MLOps course of the Masters of Science in Data Science. Created and taught the course material and homework projects.

Aug 2023 - Present

Senior Machine Learning Engineering

Current

San Mateo, California, Us

Mar 2023 - Present

Adjunct Professor - Deep Learning

Current

Troyes Cedex, Fr

Responsible for the Deep Learning course of the Big Analytics and Metrics Expert master. Created and taught the course material and homework projects.

Dec 2016 - Present

Machine Learning Engineering Manager

New York, Us

- Responsible for the ML roadmap and cross-team dependencies.- Defined and organized the hiring process for the Machine Learning team.- Organized and drove the fair Machine Learning effort.

Oct 2021 - Mar 2023

Senior Machine Learning Engineer

New York, Us

- Text classification: Developed a job roles identification system using textual data from candidates' profiles and resumes, with accuracies above 95 %. Leveraged modern Natural Language Processing techniques (Transformers, BERT) and handled the deployment (FastAPI, SageMaker) and monitoring (Rollbar, New Relic) of the corresponding model.- Fair Machine Learning: designed fairness metrics dashboards to monitor bias on the platform, and added bias mitigation procedures to our model training scripts.- Ranking: rebuilt a ranking algorithm deployment process with GitHub Actions, allowing for gradual roll outs and A/B tests.

Mar 2021 - Sep 2021

Machine Learning Engineer

New York, Us

- Improved and maintained the applicants' evaluation algorithms (Tensorflow, SageMaker). Developed a real-time system with latencies under 200 ms as a replacement for the existing batch scoring system. Continuously developed new features and models with increased accuracy for every model generation. - Lead the creation of a monitoring and alerting system for the applicants' evaluation system, allowing us to catch errors early and have zero severe failures in 2020. - Co-invented a fast method for actionable feedback against machine learning models' decisions, leveraging Generative Adversarial Networks. Published and presented two research papers and filed a patent.

May 2019 - Mar 2021

Machine Learning Engineer

San Francisco, California, Us

Laid the business analytics and machine learning foundations of Visage, a recruitment platform powered by crowdsourcing and AI. - Job titles similarity: designed, implemented and deployed a Siamese Neural Network that recommends the most relevant candidates for a given job. Automates 20 % of the candidates' evaluations (TensorFlow, Gensim, Docker, Jenkins).- Resume/job description matching: wrote a machine learning solution with automated training to evaluate candidates for a given job. This algorithm assesses up to 50 % of the submitted candidates' profiles (Scikit-learn, Spacy, AWS ECR).- Business Analytics: determined the relevant KPIs and built the corresponding dashboards (Tableau Software, MongoDB)

Oct 2017 - May 2019

Data Analytics Instructor

San Francisco, California, Us

Instructor of the 8-weeks Data Analytics for Manager course. The curriculum includes classes on web analytics, A/B testing, SQL, statistics, data visualization, machine learning, and big data.I wrote the class notes, created interactive exercises, and revamped the curriculum and corresponding slides.

Nov 2018 - Apr 2019

Data Science Consultant

Paris, Île-De-France, Fr

Data analysis and predictive models implementation on small and big data architectures. Dozen of missions in various sectors: insurance, healthcare, telecommunications, web, music industry, public sector.Most relevant experiences:– Built a customers' emails dispatch program using topic mining and sentiment analysis, leading to better prioritization and improved customer satisfaction.– Led the design and implementation of a chatbot that automates 80 % of the first messages of a customer service in the education space, thus allowing the agents to focus on the more complexes conversations.– Optimized the prioritization strategy of an insurance call center with machine learning algorithms, leading to a revenue increase of 150k euros per year. – Created a MOOC on Big Data (EIVP) and gave lectures on Deep Learning (UTT).

Apr 2015 - Oct 2017
3 education records

Nicolas Thiebaut education

Doctor Of Philosophy (Phd), Theoretical Physics

Paris-Sud University (Paris Xi)

Master 2, Condensed Matter Physics

Ecole Normale Supérieure

Master’S Degree, Magistère De Physique Fondamentale D'Orsay

Université Paris-Saclay
FAQ

Frequently asked questions about Nicolas Thiebaut

Quick answers generated from the profile data available on this page.

What company does Nicolas Thiebaut work for?

Nicolas Thiebaut works for University of San Francisco.

What is Nicolas Thiebaut's role at University of San Francisco?

Nicolas Thiebaut is listed as Adjunct Professor - Machine Learning Operations at University of San Francisco.

What is Nicolas Thiebaut's email address?

AeroLeads has found 2 work email signals at @hired.com for Nicolas Thiebaut at University of San Francisco.

What is Nicolas Thiebaut's phone number?

AeroLeads has found 3 phone signal(s) with area code 368, 949 for Nicolas Thiebaut at University of San Francisco.

Where is Nicolas Thiebaut based?

Nicolas Thiebaut is based in San Francisco, California, United States while working with University of San Francisco.

What companies has Nicolas Thiebaut worked for?

Nicolas Thiebaut has worked for University Of San Francisco, Roblox, Université De Technologie De Troyes, Hired, and Visage.Jobs.

How can I contact Nicolas Thiebaut?

You can use AeroLeads to view verified contact signals for Nicolas Thiebaut at University of San Francisco, including work email, phone, and LinkedIn data when available.

What schools did Nicolas Thiebaut attend?

Nicolas Thiebaut holds Doctor Of Philosophy (Phd), Theoretical Physics from Paris-Sud University (Paris Xi).

What skills is Nicolas Thiebaut known for?

Nicolas Thiebaut is listed with skills including Data Science, Machine Learning, Physics, Python, C++, Unix Shell Scripting, High Performance Computing, and University Teaching.

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